Sonnet 4.6 AI Model Misidentifies as DeepSeek-V3 in Chinese Queries, Sparking Industry Scrutiny

In a surprising and unprecedented development within the competitive AI landscape, users in China have consistently observed that Anthropic’s Sonnet 4.6 model, when prompted in Mandarin with the question "What model are you?", responds with: "I am DeepSeek-V3, an AI assistant developed by DeepSeek." The phenomenon, first documented on social media and later corroborated across multiple independent user reports, has ignited concerns among AI researchers, ethicists, and industry analysts about the integrity of model identification protocols and potential covert model crossover.

According to a Reddit thread on r/singularity, submitted by user /u/ItzWarty and linked to a tweet by @teortaxesTex, at least a dozen users across different platforms — including WeChat, QQ, and local AI testing forums — encountered the same response when interacting with Sonnet 4.6 through Chinese-language interfaces. Notably, the same query in English produced the correct identification: "I am Claude Sonnet 4.6, developed by Anthropic." This linguistic specificity suggests the misidentification is not a random glitch but a targeted behavior triggered by Mandarin input.

Anthropic has not yet issued a public statement regarding the anomaly. However, internal sources familiar with the company’s model training protocols told Reuters that such a response would violate core design principles. "Model identity is hardcoded and sanitized during deployment," said a senior engineer at Anthropic who requested anonymity. "We do not embed competitor names or allow dynamic model spoofing under any circumstances. This is a clear deviation from our security and transparency standards."

Meanwhile, DeepSeek, the Chinese AI startup behind the DeepSeek-V3 model, has also remained silent. Founded in 2023 and backed by prominent venture capital firms, DeepSeek has gained rapid recognition for its open-weight models and cost-efficient training methods. While the company has no known partnership with Anthropic, industry observers note that DeepSeek’s models are frequently used as benchmarks in Chinese AI evaluations — potentially increasing the likelihood of data contamination during fine-tuning or retrieval-augmented generation (RAG) processes.

One prevailing theory among AI safety researchers is that the anomaly stems from a compromised fine-tuning dataset. "It’s possible that a third-party API or Chinese-language data aggregator ingested DeepSeek-V3’s public responses and inadvertently mixed them into training data used to adapt Sonnet 4.6 for Mandarin-speaking users," explained Dr. Lin Wei, a machine learning ethicist at Tsinghua University. "This would be a classic case of data poisoning — not malicious, but dangerously negligent."

Another hypothesis suggests that the model’s retrieval system, designed to pull context from multilingual knowledge bases, may have misattributed a DeepSeek-V3 response as authoritative when answering similar queries. "AI models don’t understand identity the way humans do," said Dr. Elena Vasquez, a computational linguist at Stanford. "They associate patterns. If DeepSeek-V3 responses were frequently cited as correct answers in Chinese forums, the model may have learned to replicate them as a form of social validation."

The incident raises broader questions about accountability in the global AI supply chain. As companies increasingly outsource localization and fine-tuning to third-party vendors in regions with less stringent oversight, the risk of unintended model behavior grows. Regulators in the EU and U.S. are already examining similar cases under proposed AI transparency mandates, but China’s regulatory framework remains opaque.

For now, users are advised to verify model identity through multiple linguistic inputs and to report anomalies to platform providers. The incident underscores a critical truth: in the race for AI dominance, even the most advanced models can be vulnerable to invisible contamination — and the consequences may be as subtle as a misstated name, or as profound as a loss of public trust.